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Code Sample, a copy-pastable example

On pandas 1.0.3:

df = pd.DataFrame([7,8,9,pd.NA])
print(df.dtypes) 
# 0    object
# dtype: object

Problem description

Creating a DataFrame with mixed int and pd.NA defaults to object instead of Int64

According to @simonjayhawkins in #32931

since pd.NA is experimental, changing the constructor to default to the best possible dtypes using dtypes supporting pd.NA seems reasonable.

Expected Output

pd.DataFrame([7,8,9,pd.NA]).dtypes
# 0    Int64
# dtype: object

Comment From: TomAugspurger

We'll need to be a bit careful with this. We don't infer one of the nullable dtypes anywhere other than pd.array yet.

Personally, I'd rather wait for the global option for Series([1, 2]) to return a nullable integer. Then all of Series([1, 2]), Series([1, np.nan]), Series([1, pd.NA]) would return nullable integer.

Comment From: simonjayhawkins

We'll need to be a bit careful with this. We don't infer one of the nullable dtypes anywhere other than pd.array yet.

just to be clear, my proposal was for when a user includes pd.NA then we assume that the user is expecting nullability just as if they had specified the dtype explicitly.